The odds of accident-type casualties in a Peruvian jungle road

Angela Denisse Huaman Meza; Gian Carlos Meza Soto; Jahir Chuquillanqui Guillen; Giovene Perez Campomanes

doi:10.5267/j.dsl.2023.3.003

The odds of accident-type casualties in a Peruvian jungle road

Angela Denisse Huaman Meza
, Gian Carlos Meza Soto
, Jahir Chuquillanqui Guillen
, Giovene Perez Campomanes

School of Civil Engineering

Research output: Contribution to journal › Original Article › peer-review

Abstract

The current analysis analyzed the odds of casualties by road accidents. Hence, data were classified into tertiles for better research, and accident types were classified into five following the authority methodology: rollovers, crash, roadway departure, special accident, and car capsizing. Multi-logistic regression was employed for the data analysis. This research found that rollover was the most deadly accident, and the crash was the most probable to cause injuries.

Original language	American English
Pages (from-to)	163-168
Number of pages	6
Journal	Decision Science Letters
Volume	12
Issue number	2
DOIs	https://doi.org/10.5267/j.dsl.2023.3.003
State	Indexed - 1 Mar 2023

Bibliographical note

Publisher Copyright:
© 2023 by the authors; licensee Growing Science, Canada.

Keywords

Casualties
Multiple logistic regression
Road accidents
Road safety

Access to Document

10.5267/j.dsl.2023.3.003

Cite this

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title = "The odds of accident-type casualties in a Peruvian jungle road",

abstract = "The current analysis analyzed the odds of casualties by road accidents. Hence, data were classified into tertiles for better research, and accident types were classified into five following the authority methodology: rollovers, crash, roadway departure, special accident, and car capsizing. Multi-logistic regression was employed for the data analysis. This research found that rollover was the most deadly accident, and the crash was the most probable to cause injuries.",

keywords = "Casualties, Multiple logistic regression, Road accidents, Road safety",

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doi = "10.5267/j.dsl.2023.3.003",

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AU - Guillen, Jahir Chuquillanqui

AU - Campomanes, Giovene Perez

PY - 2023/3/1

Y1 - 2023/3/1

N2 - The current analysis analyzed the odds of casualties by road accidents. Hence, data were classified into tertiles for better research, and accident types were classified into five following the authority methodology: rollovers, crash, roadway departure, special accident, and car capsizing. Multi-logistic regression was employed for the data analysis. This research found that rollover was the most deadly accident, and the crash was the most probable to cause injuries.

AB - The current analysis analyzed the odds of casualties by road accidents. Hence, data were classified into tertiles for better research, and accident types were classified into five following the authority methodology: rollovers, crash, roadway departure, special accident, and car capsizing. Multi-logistic regression was employed for the data analysis. This research found that rollover was the most deadly accident, and the crash was the most probable to cause injuries.

KW - Casualties

KW - Multiple logistic regression

KW - Road accidents

KW - Road safety

UR - https://www.scopus.com/pages/publications/85152286857

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DO - 10.5267/j.dsl.2023.3.003

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AN - SCOPUS:85152286857

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SP - 163

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JO - Decision Science Letters

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IS - 2

ER -

The odds of accident-type casualties in a Peruvian jungle road

Abstract

Bibliographical note

Keywords

Access to Document

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Cite this